A decision support system (DSS) is a computer-based information system that supports business or organizational decision-making activities. DSSs can serve the management, operations, and planning levels of an organization (usually mid and higher management) and help to make decisions, which may be rapidly changing and not easily specified in advance. One example DSS is CLARITY from CA TECHNOLOGIES. DSSs often have a business intelligence (BI) component which contains BI rules to help with the decision making.
A DSS includes a data warehouse, one or more semantic layers, and a presentation layer. The data warehouse includes data aggregated from a number of data sources. Most DSSs typically consist of one or many data warehouses for the backend and one or many BI frontends. The data warehouses are used to consolidate data from a set of one or multiple sources over a long period of time transformed to be optimized for quick retrieval. The BI frontend(s) may be used to enable data visualization, analysis, self-service, data broadcast, sandboxing, etc.
Data may be imported into the data warehouse from the data sources via an Extract, Transform, Load (ETL) tool, for example. An ETL engine may extract data from various data sources, transform the data for storage in a proper format and/or structure for querying and analysis, and load the data into its final target in the data warehouse.
The semantic layer is a business translation layer that sits between the data warehouse and end users. The semantic layer acts as a translator of sorts by mapping complex metadata (e.g., data types and names of fields) from the data warehouse to business intelligence (BI) software fields in a way that business users can understand and utilize. Because BI software fields are more understandable by business users, the semantic layer isolates business users from the technical complexities of the data warehouse. By using common business terms, rather than data language, the semantic layer makes it easier for business users to access, manipulate, and organize information, and simplifies the complexity of business data. The presentation layer (which may be part of a BI frontend) creates BI output based on the BI fields in the semantic layer, such as charts, reports, dashboards, etc.